0:00I mean, let's be honest, software has sucked. Technology's been hard to use. Like, it's most often broken. And now we're actually in a point where this stuff could actually start working.
0:08People keep thinking of these things as software, and it's not. And I [music] think we just keep mapping it to things like search and it's not. Like, we're starting to realize how powerful this stuff is. And I just think that like the biggest [music] constraint is no longer the tech. It's literally our creativity.
0:33you recently wrote about sort of [music] four buckets of styles of investing that might be applied in call it venture I don't know big private market tech let's call it um can you enumerate those and just like say a sentence on on perspective of an H yeah yeah yeah again I feel like I'm just in this point in my career I've been doing this for a decade I've done hundreds of deals um and that I sit in these discussions and I just realize people aren't communicating very well.
0:57So I kind of did this exercise where I'm like, okay, so what are the mindsets people bring to investing? And I think there's basically four types of mindsets. So the one that um I we were talking about before is like like this traditional finance mindset, which is the correct proxy for the health of a business is the market it's going into and its finances. That's what it is.
1:16Yeah. It's like it's like what are the SAS metrics? What you know, what is the size of the market, you know, and that is a proxy for the entire business. So that's one and you know clearly growth investors do this clearly you know but like more and more you see like early stage series A people do this right which to me is is a little bit discordant then there's what I call productive investors which you believe you're investing in a productive asset and the productive asset is what's creating value and if you believe in that as it creates value it will create market and as it creates value you're
1:45going to have to find ways for the business to catch up to that value. Um, and so the type of diligence you do if you're a productive investor is more like what is the technical approach, what are the adjacence markets, you know, how fast is this likely to evolve, how close is it to capturing value, like that sort of stuff. Is this the right team to build it? Um, then there's what I call frontier investing, which is I think this is the romantic idealized version of VC from like the 60s and 70s, which is kind of yolo, man. It's like
2:13founders know better than VCs and they've seen something that I don't see and they're going to go out there and do it and like who am I to second guess them and it's about you they almost look like talent networks right like I would say Chris Dixon remember when he he was investing in neutropics he invested in soilent he invested in Oculus he invested in Coinbase and in crypto I mean it's like every science fiction trope from the 70s and 80s you kind of invest in and you just don't overthink any of these things so it's almost like the strong form of the productive and
2:41then the last one and it is always so surprising how prevalent it is is speculative investors which they don't even care about the asset. They just want to time a market, right? And so like you'll see this like in crypto and in secondary markets where they don't know about the underlying asset. They probably don't even know about very much about the actual like business metrics, but they're like, "Well, this looks cheap. [laughter] It's clearly going to go up in value. Oh, this is the top of the market, you know, like I'm going to get out." And so they like they're try they're trying to like time markets.
3:11they're they're they're they're actually just doing speculative. They're not not really interested in like will the business grow. And again, the problem is is if you have all of these arc types, but you can justify any deal or not justify any deal. So, if you don't know what your beliefs are, you'll always basically just kind of justify whatever personal bias you have.
3:28If you think about yourself as a productive investor focused on disrupt, I love this idea that disruptive technologies, you should not look at these some of these traditional things that so many investors talk about. talk about what you do look at like when you're looking at you know you look at so many companies what is your method by which to assess whether or not someone might be creating a truly disruptive piece of technology a really a valuable asset so I only do computer science investing and I only do infrastructure investing
3:57and I think infrastructure as an industry has a certain shape right and so it's not like you know it's got certain buying behaviors the technology looks a certain way and the industry acts a certain certain way. And so what you're trying to do is you're trying to take a technical approach and you're trying to map it into that technic framework, right? Like this is kind of what we try and do. And and the way you do that is is you know there's a number of approaches. One of them you're like what are the leading companies doing
4:25internally and this will kind of give you a glimpse on like maybe this is how platforms evolve or perhaps the team that is doing this had had did it in another context and now they're actually bringing it to this context. I think it's one of these things where like how how much can you diligence without actually just using the numbers for a proxy as far as you know you can talk to customers will they use this you can see if there's like adjacent budgets that you know you could that are growing that
4:54you could kind of argue will fragment to become this or maybe you have early signs of willingness to pay but they actually haven't figured out the business model like I always I always think like every tech wave I've I'm you know I've been in the industry for 30s every tech wave people like hand ringing about margins everyone like I remember for the cloud I remember for mobile I remember for the internet you know clearly now people worry about margins so maybe you're like there's a willingness to pay and there's a lot of interest but like we haven't figured out the cogs yet in the actual
5:24viable business model so like you're using partial indicators not full indicators in order to do this and so my team I mean my team has a lot of you know technical people product people many have PhDs and like listen we don't second guess the tech like the founder will know the tech better than us. But but we can ask the question, how does this tech fit into the broader platforms? How does the tech fit into spending? How does this um uh tech fit in with our understanding of stickiness and defensibility? And then we look at early market numbers and we'll say,
5:53"Hey, listen, like no, like this is like a financial investor would puke at this, but like it actually shows that the customers are really interested to figure something out and will they be able to figure something out?" now. So, there's a lot of diligence you can do where with frontier investing, I don't think you do any of that. You're like, it's people.
6:08Is this [laughter] like it's it's it's people. Is this the best team to do this crazy thing and then you just yolo?
6:13You were saying before we hit start that nobody understands network effects. Can you can you explain what you meant?
6:19I've realized that like like even the most common terms we use there's no consensus on. And so, for example, network effects is the favorite one that I pick on. Like I asked you before, I messed it up.
6:30No, you didn't mess it up. You said you said what like like a third of people say. So I said so what is a network effect? What did you say?
6:35I said a product that gets better as it adds a marginal user. So to me this is almost a tautological definition because most products will get better as you add a user right like you they will find a bug they will provide feedback they will tell other people you know and so that doesn't say anything about defensibility but other people when they use the term network effects they actually mean the original meaning of the term network effect from the 70s which is a telephone network where when users join they interact with each other that grows
7:04super linearly and that's why you get like natural monopolies And [snorts] other people use the term network effect more to mean like an an actual flywheel. So like a self-reinforcing flywheel. So not just like things get better, but like it self-reinforces in some sort of a way.
7:19This where you hear the term like data network effects. But even in that sense like you don't know if like that self reinforcement is super linear or not. So you don't know if it makes it defensible or not. So you have this very common word that's on 70% of pitch decks where a founder is sitting in front doing a pitch and nobody has consensus on what it means.
7:39So how would you define it?
7:40So I think the root of the confusion is not is is not a definitional problem. I think the root of the confusion is conceptually we conflate the mechanism with the shape of the moat. And I'll let me explain. So um there's many things that could create a moat, right? like a brand uh scale, a two-sided marketplace, a network effect. But that moat to reason about that is only really useful um if it has some properties that that
8:10that makes the company defensible against somebody else, right? So if that moat grows superlinearly with scale like a classic metaf's law network effect would, that's really defensible. If it grows sublinearly with scale, it may not be useful at all. And so I think so you and I have a conversation of defensibility. I think the first thing we need to do is not conflate the shape of the moat with the net mechanism that caused it. So first I think we should say the moat that we have is super
8:38linear. It's linear or it's sublinear with scale. And then the second thing a lot of things actually contribute to a mode right to that like for example like we mentioned network effects will or scale effect. What's a scale effect? The scale effect to me is as the companies scale it can reduce unit economics normally because it has pricing power for example or maybe CAC goes down because of brand. Um what's a two-sided marketplace? That's very different to me than a network effect. That's where basically you've got you know self-reinforcing supply and demand. So I
9:08think that there are many mechanisms and then there's the shape and then then to have a discussion I think you want to make sure that the shape um is something that actually provides long-term defensibility.
9:20Then the last thing I'll say is it's it's almost impossible to have these conversations in isolation because we're actually talking about competitive equilibria because if you have a network effect then maybe the the competitor has a network effect too and maybe if they have more capital than you and grow faster that probably like impacts the shape of your mode, right? Like you may go from you know like uh you may not grow as fast marginally because they're stealing your customers or something like that. And so I just think that we need like very very basic concepts. We
9:48need to not conflate the notion of uh of the actual shape with the actual mechanism. And then I think we should actually like enumerate the mechanisms because something like the definition that you had just doesn't really help anybody.
10:00Can you give examples of superlinear linear sublinear just just to bring it to life?
10:05Yeah, for sure. A common view of where network effects came from was from the 70s. I forgot the name of the the the economist that did it, but he worked at Bell Labs and he noticed for like train networks and communications networks, the interactions of users grows with the square of the number of people that join, right? And so as a user joins, they can communicate to many other people. So the actual number of connections grows more than the number of users. And then you know therefore
10:33the value grows more than just linearly with embedding. The same thing with like destinations on a highway or destinations on on a train. So So that would mean that if you have two competing companies and one takes, you know, $5 million of funding and the other takes $5 million of funding, but this one is marginally better, marginally larger. This one's a little bit larger. For the same amount of investment, it will grow faster than a challenger, right? So like the growth actually increases over time and that's
11:02why you get that's why you get a a monopoly. Whereas sublinear means if I'm a leader and I invest the same amount as a challenger, I grow marginally slower than the challenger. That would be sublinear. And clearly this is very important when it comes to modes.
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13:11Do you have like favorite company recent company examples of these different types?
13:14So I would so actually I would so so how many actual network effects in the metaf's law of super linear do you think there have actually been here?
13:22Very few. I don't know.
13:23I I I feel like this almost never happens. Like I think we can all agree the telos. Yeah.
13:28That's why we had to break them up. We could probably all agree LinkedIn like you know like they haven't had to like change very much and they seem to you know you know basically have a a permanent status social networking and but all of these examples it's like the interconnections of people I would say GitHub was another one that had a which was effectively interconnection it's interconnections of users right um so I think there are not very many examples but when you have them these are these very durable highv value
13:56companies right so that to me would be like a classic network effect. I would say other companies probably are more scale effects, right? Like for example, people will say Uber. I'm not sure that that would fall the definition of a network effect. Maybe a two-sided marketplace because you have the drivers and you have uh the passengers. Maybe you could use that, but even then you don't have a lock on either of them.
14:18Like all drivers drive for everybody and all passengers could use anybody. So that seemed like that was more like of a funding scale effect just because they could raise more money and therefore the unit economics went down. And so you know I my my meta observation. So first off I actually think the network effect thing was more of like a personal annoyance and me being a a pedantic but I actually think defensibility most is kind of um it's not really even worth talking about most of the time. Let me explain why. So um here's my experience
14:47for what it's worth. If a market you're investing in is growing, then companies are not going to want to compete. There's like a lot of new white space that gets created. And so what they'll try and do is they'll try and just move into other white space. And so talking about defensibility is kind of a second or third order thing if the market is growing.
15:06And if the market is slowing down or shrinking, normally it consolidates anyways independent of Moz or not. And so I do think we spend a lot of time as investors hand ringing about defensibility when in practice uh it doesn't really matter especially in growing markets which we invest to and we've seen this with AI like I remember early discussions on models. I mean I can't tell you how many investors are like I will never invest in a model.
15:31It'll never acrew value. It's not defensible. That's fine but as long as the market's growing in a large market it's going to acrew a lot of value. I remember this about the Neoclouds. They're never dependable. the quality of revenue is bad, you know, and so, you know, and so I think that we kind of trick ourselves as investors by thinking in terms of defensibility when if there's a growing market, it's kind of not even worth considering.
15:53Do you think that's a unique uh privilege of your stage of investor and then you know once you get later stage public like someone that's buying the anthropic S1 needs to probably think about defensibility.
16:06I mean it depends on on your thesis on the size of the market. I mean if you believe we're 0.1% penetrated like you know this has got a long way to go and and value will acrue and if you're liquid you can go in and out of the market if values acrews I mean I think that would you know I think the nature of venture has really changed actually in in general um you know if you read back kind of you know the time of like you know Arthur Rock it was really frontier- like investing and people
16:35didn't think about quality of revenue you know they didn't think about defensibility so much it was people and it was tech and it was new markets and you know over the last 30 years like the tech market has grown so large and the amount of money that's available to investors has grown so much and then the size of the private companies has grown like a like a like a private company today rivals public companies of just you know 10 years ago and so I say in some level VCs have actually become
17:03public investors right and then a lot of the people that have entered VC have come from like more business school and traditional finance background. So I think a lot of the mindset comes from that world, but I think it gets applied too early.
17:17The financial mindset gets applied too early.
17:19Like a traditional investing financial mindset gets applied too early. And I think it's kind of confused. I mean I I it's very often, for example, I talk to like a junior investor and they're like, "Oh, the quality of revenue is bad." I'm like, "Homie, we didn't even know how to monetize the internet." Like like business models always lag disruptive technologies.
17:40Always. Right. And so like you can't if you if if you truly believe you're investing in a disruptive technology and that's what you truly believe in. A you should believe it creates TAM. So why would you worry about market size cuz it's creating market size. Um and B it's disruptive. So we don't even know what the pricing model is. Like remember like how long it took for us to go from like perpetual to like recurring? that [laughter] was like years of like whatever and hand ringing etc. And so you know I mean I think my caution is
18:08like maybe most investors should know what kind of investor they are like maybe you're a financial investor and like that's how you view the world but then you're not actually evaluating tech. You're not evaluating the the the disruptive power of tech. You're literally looking at the quality of revenue which which by the way is going to naturally move you towards non-disruptive technology because if it's disruptive you probably don't know what the business model is. you probably don't know what the TAM is.
18:33On the other hand, if you really believe you're in like if you believe I invest in tech and tech creates value and that's the type of investor you are and you do that early, you you should not consider these other things. Um and so I I think it's less about is there a right way to invest? No, these are all legitimate coherent right ways to invest. It's more about don't be don't be confused in your basic kind of approach because otherwise you become incoherent and so then like you're like oh I'm a disruptive tech investor but I'm looking
19:02for like whatever good NR like it it doesn't work that way.
19:05How would you describe the state of the union today in your world in infrastructure like um obviously it's changing really really fast. There's new kinds of companies but there do seem to be like some uh we could like name some layers or some categories. How how would you describe like what it looks like today?
19:20So for me, so the definition of infrastructure is like the the the differentiation is actually technical where I don't view SAS or apps as that way. Like do you view like if you invest in like um like a SAS or apps company as like a technical investment?
19:36Right. Cuz it's like a business now.
19:38Yeah. Especially now. I mean it's like a business model innovation or or or something like that. And so so because for us as a technical innovation it has to sit kind of within the traditional technical stack. So the traditional technical stack for infrastructure is compute network storage and databases right and each one of those has a subcomponents and they all have buyers and they all you know now we're seeing that being kind of reformed with AI a bit and so all of them are being disrupted but also now you have um models which I would consider infrastructure. They look to me more
20:08like A6 than they look like um you know traditional software. I mean like the capital needs the you know the competitive pressures on them and then I think they're disrupting the entire application stack above them. Like we don't even know if they will layer like we don't even like I mean maybe you could argue with Jeff they do kind of you know you can kind of put them in software but traditionally they're almost like you know their own separate entity that's that's that you can't marry to software very well. And so I would say we're in kind of a point of
20:35maximum disruption, but all of the infrastructure supporting software whether it's vibe coded or not or whether it's to build models or not. I mean that doesn't change like the the the major components. And so I think we do have a bit of a traditional mindset of [snorts] compute, network, storage, databases and then models. Yeah. And then and then and then but we also throw up our hands. We're like this is all changing so fast because for example when you worried about dev tooling in the past you worried about ergonomics for a human. No, you don't really worry about that. And then actually a lot of
21:05the design decisions that we made as technologists were like, well, a human's going to be using this so it can't be too complicated. And then you would trade off things like safety or you trade off things like reliability. We don't really have to do that anymore because the models are doing it. So I think this is kind of the biggest refresh of computer science infrastructure we've seen maybe since the internet maybe forever.
21:21Would the shorthand for this be that all the each of those five portions of infrastructure are being refactored for agents? Is is that like overly simplifying?
21:30I split it in two pieces. For me, there's like people are vibe coding a lot of stuff. There's more software being written than ever before and that stuff has to run somewhere and that has nothing to do with like that's not agents. That's just normal software. Maybe it's an agent that created it.
21:44Maybe it's a human being created it, but like it needs databases and it needs compute, right? So that's one thing. And so I just view like the it's like the product of agents. And then the other one is like we're building these new systems that are kind of that have AI at the heart of them and then how does that change it? Those are the kind of two. So just assume way more software being built and has to be run and deployed somewhere and then think that now we also have systems that like actually create agents.
22:07It seems like each new wave of technology like there's a new kind of database that's needed.
22:13Are you seeing that across all the areas that you care about that there's sort of because of AI whole new entrance?
22:20I think a lot of infrastructure is getting a bit sleepy and now because agents are very sophisticated that's no longer the case. Like so for example let's take OOLTP. What is OLTP? LTP is a transaction database like think the oracles of the world. That's a pretty mature industry. You didn't see a lot of movement. Maybe you saw like movement to the cloud or something like that. But now we're seeing really interesting companies that are like, you know what?
22:42Um the hard thing about using a database from a programmer standpoint is databases always had their own languages and they've had their own languages for technical reasons and it's really really hard to to have them work with normal programming languages. But now because of AI and and and one of the reasons is like if you if you change that language like anybody that knows databases would know how wouldn't know how to use it and you'd have to like train a whole version of um of programmers to use this new language. But now we're actually seeing
23:11databases come out which are entirely new way of thinking about databases which have way better properties. They don't really have to train anybody because the agents already know how to do it. And so you know I think these things are path dependent like some comp some sectors a new entrance is going to come and change it like databases OLTP may look entirely different in 5 years and some the incumbent may figure it out and be like hey listen we're just going to add a few things networking of course which is listen I did my PhD in networking so it's an area of like special interest like that's been so
23:40sleepy and boring for the last 15 years and now because these clusters that we're building are so large and they've got like such um you rigid performance constraints. We're seeing, you know, net new networking companies come out for the first time since Arista. Um, you know, we're actually having to change, you're seeing like actually, you know, changes in in the materials used to build them. We're seeing optical come up. And so there's a lot of interesting stuff in networking compute. I mean, you know, the whole notion of like what are
24:09the abstractions to to run an agent on? Is it like a container? Is it a VM? Is it a durable workflow like something like temporal like that is changing but I do think we're at a point of maximum disruption where many points of the infrastructure stack can be rebuilt.
24:26Can we spend a few minutes on models?
24:28Tropic S1 came out this week which you know obviously a a beautiful view into the business itself. But I'm actually more interested because the infrastructure stuff in what you think about just the state of these things today. I'm interested in all the debates closed versus open um the public frontier versus the private frontier that the model the companies keep for themselves you know movement of talent opportunities things that don't exist that should like whatever whatever's on your mind about these things and how you see them evolving I'm I'm fascinated to
24:58hear so I think the biggest question is is what happens if and when the market slows down because I think we've got three years of data of what happens in the existing very big fast growing market and like what happens there is the frontier being on the frontier means you've got tremendous pricing power even if you're just an epsilon better than the next guy you got tremendous pricing power there's no demand problem you've got basically infinite demand and so like these kind of frontier models that
25:28are the best tend to get 80% plus of the market dollar weighted and that's happened for 3 years right but you could argue the reason that's happening is because we've not saturated the market at all and people is going to want the smartest thing. And so then under that view, there's nothing structurally going to change as as as long as the market's growing. And you could argue this is going to go on for quite a while because I mean, what is it penetration? 1% or something like that. They say 3% of the enterprise, but actually from budget- wise, it's like 1% or less, right? And
25:57so there's just a lot to grow given how useful the technology is. The more interesting question to me is okay, like what happens if the market starts to saturate in pockets, right? So if that happens, you know, will then things shift to open source? Will you lose pricing power on the frontier? You know, one thing that we don't really like do a good job of accounting um for when we model out the numbers for these companies is you know what happens if
26:24you invest in a model and then like you don't get the next model out really quickly, right? Let's assume that like Anthropic stumbles and they don't release a model for 6 months. What is the lifespan? Do you think of the previous model?
26:37A very short period of time.
26:38It's very very short, which is entirely different than we've ever had in software. In software, we've always assumed some long tale. But it turns out like what what happens if like you know like you put out the soda model and everybody loves it. Then something internal happens. I don't know if it's regulatory. I don't know if it's technical. I don't know if it's a breach. Whatever. And then you slip three months, right? It could be the case that you lose the entire market. I mean my experience and I see a lot of these model graphs from apps companies and from you know pitches I would say that the lifespan of a model is three to six months. So that means you you have
27:08to release the next model. So again for this conversation I think it's a very interesting conversation. We should tease it apart like what happens if the market continues to grow and doesn't saturate. I think we already know because you have three years of data.
27:18You have three years of data and it just means the frontier wins and they do a great job and they create great models.
27:23Then what happens is if either the use cases saturate meaning you don't need more intelligence or the markets start slowing down for another reason. Nobody knows the answer to that. I think there's a very real world where this the value comes crashing back down into open source and you know we'll see kind of like a shift that we've never seen because software has always had a long tale of retention.
27:43On this trip I've been asking a lot of people what percent of software coding tasks are already saturated and the typical answer is very very high percentage. that's been the biggest market and yet it still seems like people are spending like crazy on Frontier tokens to do coding which it it seems a little at odds like if I could do it with a six-month old model or something that's vastly cheaper.
28:06Well, these are two different statements. I think we need to be very this is a great thing to dig in on but we need to be very careful when we're talking. Please tease it apart. Yeah.
28:13Yeah. This is great. Great. So there's two very different statements. So statement number one is I am not using more tokens, right? Because of I, you know, I have enough I I I have enough tokens. I've automated 95% already, so I can't automate anymore. That's and I think that we're getting pretty close to that. Comment number two is therefore I can use a cheaper model does not follow from combat number one. Right? So if you and I are are like I'm uh uh you and I are competing startups. We got Martine startup and we got Patrick startup.
28:41Right? We've got competing startups and because we're in competitive equilibria, are you going to choose a dumber model to compete with me?
28:51In competitive equilibria, you wouldn't.
28:53You would always pay 10 times more for the smartest model. Yeah. Always, always, always. And so, you know, there's this very open question of um will you saturate tasks so that you don't need a smarter model? And I think it's very hard to do that in a Darwinistic economic equilibria like you know and when when you're actually competing and so some of them may but I think at the end of the day it's about can you get software out faster can you make it better and can you compete in the marketplace and that will
29:22necessarily push you the the more intelligent thing. Now that said, clearly things will slow down because you're actually not spending more tokens. And so either you have to increase prices or you're going to have to go broad. But in my experience, the pricing is maintained for sure and because of the competitive equilibria like you always want the smartest thing. And then we're just seeing like like a broadening use of these outside of code, right? So general knowledge work like I'm a huge Grockpa
29:51user. It's like my favorite thing ever. And so I think we're starting to see Yeah. take over more and more of these.
29:57Say more about your personal experience with that. What you're learning, what you're doing with it, what you're learning from that experience.
30:02My my new Gro. This is so funny.
30:04I know you have a home automation thing going on.
30:06I know. It's so good. Like I just feel like I've waited my entire life for this technology to show up, right? Like I want Star Trek. I want to go home and I want my house to greet me and I want to talk to it and I want to have the face show up on the monitor and and I want the whole thing and like it's never we've never been able to do it and now it's kind of trivial. So I use Rockbot for a lot of stuff. I use it for personal finances. My big hobby is modular synthes like I like synthesizers like making music but with like the
30:341970s like patching tweaking type stuff. It helps me with a lot of that stuff.
30:38So, I use it for a lot of like standard things, but my new kind of passion project is um I want Grockbot to embody itself. So, [laughter] like what I what I tell it, I'm like I say, um I say, you know, I want you to be the living AI in my house. That's what I want. And I want it to be just like Star Trek. Help me make this happen. And it's literally buy stuff. [laughter] Buy stuff. So, I was like, "Oh, let's try this." So, like yesterday, I bought a few hundred worth of gear that's coming to the house and like I'm going to have it embody itself. So,
31:07so what gear is it buying?
31:09I don't [laughter] I don't even know. It's like these weird like these weird open- source projects and like I mean it's like this really obscure like I know some home automation stuff like I know like Ziggby Life. I know some home but it's like really obscure stuff that it's decided to to buy. But like like I I I I just have in my head this vision of like you know you know like that kind of like vintage that kind of vintage view of what the future looked like like the ' 70s view like you watch the house. Yeah. Like, yeah. Like,
31:38I mean, I just want that. And so, like, I've basically just been kind of feeding it pictures and descriptions and I want it to create that by itself. And so, I I'll let you know how that goes.
31:47What is this and other experiences using this technology since you're probably in the 0.001% of, you know, creativity using it?
31:56What does it tell you about what's coming?
31:58Yeah. No, this this is it. I just feel people keep thinking of these things as software and it's not. And I think we just keep mapping it to things like search and it's not. And we really have created general flexible technology that can bring us like of many of these future things that we've always dreamed about, you know, but like you know, you just didn't have the technology to implement. And I just feel like we're so constrained from our presuppositions of what software can do that people aren't
32:27doing as many of these things. You know, I'll give you another example. You know, I worked with FY and World Labs, great company. Um and one thing I I realized as part of that and what they did is they created you know they created a model that would generate you know 3D scenes and you know you know they released a model called Atlas um a few months um ago and you know that would like like generate basically any scene but also supported dynamics so it would move and I realized you know we're this close we're this close to being able to step into a movie. I mean, like, imagine
32:56like, you know, Miyazaki probably wouldn't be happy with it, but imagine like having Spirited Away running and you throw on your VR glasses and you walk in, you know, and like you're there and like um did you ever see Sleep No More? Like the Of course. Yeah, I went to it.
33:11Like, so like why why isn't there a Sleep No More in VR that, right? That you're walking in like the whole thing is going on and like just for those that are listening, Sleep No More is an immersive play which is 3 hours. it was in this kind of three-story hotel or something like that building in New York and you're like running around trying to figure out and like like like Hamlet is being played out or whatever.
33:31And so I just feel like like like we're starting to realize how powerful this stuff is and that that a lot of like these tropes and visions of the future from like the 50s and 60s we can actually make. And I just think that like the biggest constraint is no longer the tech. It's literally our creativity. And it's just because we've been beaten down by 30 years of software being I mean, let's be honest, software has sucked.
33:56Technology's been hard to use. Like, old people hate it. Like, it's most often broken. And now we're actually in a point where this stuff could actually start working. And so, for me, it's like I'm so excited for what this brings.
34:08It's tempting to say you could just freeze the models and their current capability and still get all of what you described. So, there's like a diffusion question I'd like to explore. But before we do that, what, if anything, do you think is missing from the models? like how do you hope or wish or dream that the models themselves continue to get better? So, so I think again I think if you step back and you look at like what we know as an industry I feel the current tech stack anything that's digital I think with enough capital you can solve right and the reason is is
34:36because anything you can simulate on a computer you can create RL environments for whether that's 3D using Blender whether that's general application use of a computer whether it's code um so you know and you and I have talked about this before I think when it's all said and done the most interesting thing about AI, the meta thing is that like you can take a money kid and then you can point it at a problem and it will solve that problem. Like maybe it's expensive, but at least you can solve it. In the past, you know, you'd be like blocked in engineering and you'd die,
35:05but like now you can actually just direct money at problems and solve these problems. So I feel very confident saying anything in the digital world because you can because you can create an environment and you can RL it and you can train on it, we can solve. So I just feel very comfortable. Anything you do with a computer, AI will be able to do.
35:21So maybe it doesn't do it now, but like you can just see that path happening.
35:24[snorts] What I don't know is does the same thing apply to like the physical universe, right? You can't like sure sure you could set up a lab to like Nick speakers or whatever, [laughter] you know, to do that. But like are the scaling curves the same, you know, is the distribution the same? So anything to do with like robotics and the physical world and science and medicine, I don't I have no idea if it follows the same laws. And so I think that's still an unlock. But I feel very comfortable that the current the current the digital side is done. I mean it's done.
35:52How have you processed all this interesting security stuff breaches uh I've heard it called breach apocalypse. Uh it it's obvious that we're like entering an interest a very interesting era in cyber.
36:04What what do you make of all this?
36:05I lived through on the ground you know with formal studies in security. I lived through the internet and it was way worse than this. Like if you like by this time with the internet, you know, we had worms that had caused, you know, billions of dollars of uh economic damage. We' taken out critical infrastructure. I I remember when it was Remember Windows 95? You're probably too No, I remember. Yeah.
36:31Okay. Remember Windows 95?
36:32Barely, but [laughter] so it used to be that if you took Windows 95 and you installed it and it was connected to the internet before the installer was done, it'd be infected.
36:42[laughter] like it's been taken over like not a joke, right? Like and so like you didn't even have time to patch it, right? And so like it was just like so chaotic and there was so much mayhem and like this is what happens every time you've got a new technology that that changes the nature of how we run computers in the security posture and we're definitely dealing with another one of those moments. And so I think we can look to what happened with the um uh with the internet which is like there's a few
37:10years of mayhem. you do have breaches that cause real issues and then you know the industry evolves and and normally the way you think about security is like will the good guys be able to spend more money than the bad guys if the answer is yes which is typically the case you will come up with a technical solution and I think that will be the case here and you're already starting to see it I mean like the these vulnerabilities that you see showing up this is good that means that somebody used the model to like make things safer by pointing out the vulnerabilities I think this going exactly like you would expect it to go
37:39but I think the net impact will be that software will be much much much more secure because AI is also securing it.
37:45Can you talk about capital like what your sense of there's very interesting things happening in capital markets rate you know the the the rate line for our whole lives looked like this and now it looks like this and there's clearly lots of demand destruction happening there's clearly many companies that 5 years ago we would have what does that mean demand I don't know what demand destruction means meaning like we're not funding things that we would have in a different environment because the cost of capital to fund them is too high because and the cost is rising because the returns are
38:14so I on anything AI. So you've got these I was looking at this company this morning where if you and I had seen the deck 5 years ago, you'd be like this amazing like software business and we should fund it. And now um it seems to pale in comparison to other things that we could put our capital to. Capital itself feels like this interesting variable in this whole equation as a constraint. And I'm curious how that feels to you. What what comment?
38:37So um I sit on the boards of a lot of great companies that have the problem that you have. profitable growing 40 50 60% at scale but like they're like say 300 400 500 million in AR what do those companies do right you can't really IPO because they're subscale but they're great companies and I think about my own personal portfolio I'm like whatever I'm in MUN bonds man I'd rather be in these companies right and so does it does it like I think that everybody would be
39:05happy with an asset that grows 40% like you would be happy with your personal money being in that you could guarantee it. And so I still think these are very good companies.
39:17And so I feel it's more a question again this is my naivity of not understanding this of like are we going to see a shift in the market so that people can get exposure to this asset class because I think the risk profile is very very different than AI. Nobody knows what's going to happen to AI when the market slows down. Nobody knows, you know, like it could be easy come easy go. It could keep going forever. Like nobody really knows. And so the only free lunch I've ever seen in investing is diversification. And I would love to personally have like
39:47a basket that includes these slower growing, but like these assets that don't like disappear if they like miss.
39:54Are are most of the ones though that that are in your mind extremely subjected to this disruption risk?
40:00meaning like I I I won't name specific companies, but there's lots of companies with that kind of rough profile which seem uh terrifying in the face of like how easy it's going to be to create software.
40:11So, I'm an infra guy. So, for me, more software means you need more infra like like like we haven't seen a big dis like we don't vibe code databases yet like you do if you're a database.
40:23Snowflake be a well-known example of kind of what you're talking about.
40:26Snowflakes a yeah it's a great example.
40:28I mean like this is like it's really hard and it's not just building it. It's really hard to have the long tail of features, the long tail of performance streaks to actually operate these things is really really tough. And so let's say that Snowflake is growing 30 to 40%. And the economics are good. Like if I just think about my own personal like I don't think that they're at any risk of being disrupted by AI like maybe by data bricks but that is like preAI type of thing. And so again again I'm very naive when it comes to these things. I'm a very simplistic thinker. My view is like
40:57I don't think AI is going to disrupt these. I think they are good businesses and so I think more and more the industry is going to want to like wrap these up and get exposure and I don't know what that looks like. It's kind of interesting like we're even seeing spaxs come back. I get a lot of calls now for companies I sit on the board which are good companies where these spaxs are like hey listen like we can you know we can make this stuff go public. So I think that the the financial markets have to figure that out. I personally like there's a lot of companies that will be disrupted by AI but there's a whole bunch that will not and I just think the market doesn't know what to do with them right now.
41:26Most meetings that you have around here in the LA at least for me in the last let's say 3 months some half the meeting is about compute and that the product across categories like just needs more compute that is available to accomplish its goals. So this is another way of asking about the capital thing. Okay, interesting. You guys manage a ton of money. Um, everyone's deploying uh their funds at very fast paces.
41:51Each company that's working requires lots of capital. I'm trying to get a sense of the feel of how much capital itself is the constraint that like if we just air dropped a trillion dollars more in all the funds like yours, that would be a good thing.
42:06Great. Great. Great. I think this is great. Um, uh, okay. So, I I really think and I I said this before, but I'm going to reiterate because it's so important. I really think the big disruption of AI is the fact that you can throw capital at problems. In the history of like tech, you haven't been able to do that because it was always an engineering problem, right? Which just doesn't scale. The mythical man is the mythical man for a reason.
42:30And so, in 10 years ago, if I had, you know, five founders show up and they asked for a billion dollars and I gave it to them, what would happen?
42:37Sits there or they would detonate, right? they like hire [laughter] a bunch of engineers then you're really right? Like I mean like it just you can't you can't you can't throw capital in but but but now I Sorry. Can you explain the mythical man month? That's a very interesting idea.
42:52Yeah. So the mythical the mythical man month basically says that you can't increase the speed of engineering.
42:59There's like a natural loar. [laughter] It's very sublinear and it has to come with like basically like organizational communication was one of the conclusions. But the takeaway for those that are listening is that this comes from I think Fred Brooks right in the like the 70s which is basically like you had these software projects and you wanted to get them out faster and so they would throw more people out and then it would go slower right and so like engineering has always been this bottleneck and in my experiences and I had my own startup I you know I did it for 10 years right it ended up being a
43:27very large business this is totally true right it's just you can't scale engineering and to me the biggest shifts like if you step back like industrial revolution level shift with AI is I can take 20 people and I can give them a billion dollars and they can use that.
43:44Now do they make 500 million from that billion or two billion? I have no idea.
43:48But the fact that you can productively use that money is so new and is so interesting. And so at some level the capital markets need to figure this out because like they are you know taking this money and using and if you look at anthropic and open AI they've probably raised more money in aggregate than the entire downstream ecosystem combined by a factor of whatever. So like I mean they are these kind of mechanisms of turning money into growth. So that's one side, but there's another side which is the debt side, which is which is quite a bit different than the equity side,
44:18which is I do think the currently I'm not a I'm not a a growth investor, not a public markets guy. I'm not a debt guy, but here's here's what I'm seeing on the ground is um we're running out of available debt. And if you're like whatever the Norway pension fund, are you going to like give debt to random Neocloud or like buy T bills, you know?
44:40And I think that we're just at a point where like you just don't have you don't have enough money to go around and so it's going to prefer the investment grade companies and then those that are not investment grade will have a harder time.
44:53So scale wins again.
44:55So yes, scale will win and then then it'll be a harder time raising debt. So if like if your business model requires you to raise debt, there's just not enough debt to go out. So I think like I know you're talking about capital as in like like like general capital to fund and I think that you know you're going to see a ton of liquidity. I think that that feels fine to me. The debt side I I I don't know these markets but I definitely know it's harder to get debt now.
45:18And I think what this will mean was like um if we want to have smaller players around that are not IG that get debt, they're going to need to prepay which means their customers are going to need to prepay. I think over time this all kind of flows back to like the availability of cash and capital because you do have limited amounts of debt.
45:35This reminds me to ask about sort of Neolabs, NeoClouds, inference uh providers and companies this I don't know if you call these infrastructure or what part of the stack you call those all as infrastructure. So if you take the you know those kind of categories in turn there's there's lots of them lots of them have been funded very few of them are are sort of at scale and I'm curious how you think this plays out like what roles they should and will play uh what the market feels like these
46:05things are growing so unbelievably fast in most cases.
46:08I'm very interested by these companies and I'm curious what what you think of these categories. Well, let's put it Neolabs aside because I think that's the least well- definfined of all of them.
46:16I included them to be clear because so many of them seem to be building their own.
46:20They're becoming they're becoming Neoclass.
46:22Well, like every pitch so many pitches turn into some version of like we're building a token factory with some degree of vertical integration, you know, and and some Neolabs are going all the way down to like buying land and power and all the way up through the token, you know what I mean? So, there's this weird Yeah, I think we really need to So, in my world, that wouldn't be considered a Neolab. That would be it. Like all neo clouds want to be token factories. So I would view of like your output is like a token of an existing model or something. Yeah.
46:49Yeah. Then you're you're you're a Neo cloud. Like all of them want to do that and they will all verticalize. Um I mean listen I really think that the actual real limitation right now is is hardware supply. That's the it's not capital.
46:59It's not debt. That's the actual real limitation and power. So Neil cloud to me is one that actually provides like the physical infrastructure that ends at tokens, right? And so they could provide GPUs, they could provide um you know you know fine-tuning services or they can provide tokens. But it's like think of like a data center that actually has the GPUs in it. That's what a neo cloud is to me.
47:19A neolab to me is give me a billion dollars we're going to come up with a new model architecture and I love a lot of these business plans are like if we solve ASI that's our business model. like literally like that [laughter] that's like literally like you know and so like these are like these kind of like and by the way to be fair that's what open AI's original thesis was and and to some extent anthropics which is like if you solve the intelligence problem the business model part is easy so that's to me a neolab is new architecture model training and they're you know and sometimes they'll buy their own
47:49infrastructure and buy their own GPUs but like that's not what they're building towards or selling right so back I mean I think that the entire like the real constraint right now is power it is it is chips it his materials like that's the sort of thing and I I think that with that sort of a limitation 80% of these things are going to go to the scale providers and you know 20% are just going to be kind of hard-to-reach places nichy type places you know like I
48:18have the relationship with a random government that has the power that's kind of funny I've met this company that it does basically in you know a GPU marketplace that's what it does and like it's but it's like the most like low-level version of it and like many of like their GPUs like converted like chicken sheds you know like like like little like chicken coops where like people like in farms are like you know just like finding ways to provide it. So there I think there will always the market is so large there will always be a significant portion that it [snorts]
48:48just doesn't make sense for the SpaceX's to do like SpaceX is not going to go and like you know find out how to create a marketplace of like chicken coupe GPUs right and so I I think this is what is end up happening is is the 20% is large enough to have a very wide fragmented array of folks but then the 80% of the market are going to be these kind of homogeneous you know things like SpaceX.
49:07I heard this story recently that someone asked Larry Pageige how much of compute will be orbital and he said 59s and and the reason was it's just physics like eventually it's just like all going to be in space.
49:18You know what's so funny is like the actual space thing actually pencils out but the reason it makes the most sense is just regulatory just because it skirts it just Yeah. Yeah. It's just b it's basically regulatory. I think there's 500 proposed legislations to stop data center building in the United States alone including Texas, right? like if you can't build a data center in Texas, I don't know what we're doing anymore. And so I think like if that regulatory pressure continues and you actually can't break ground and I've heard from many of the top data center people like it's very tough to break ground right
49:46now, then either you go international or you go into space.
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51:07Your comment on, you know, these kind of software companies growing 60%. reminds me to ask about prevailing valuations in the market and as a productive investor that's focused on disruptive assets being created. Even if the disruptive asset is truly incredibly valuable and great, every one of those has a price that will ruin the return of investing in it if it's too high.
51:29So, this is another one of my bugaboos, which is um I think I listen I don't know how you can be a VC and not believe tech creates value, which is the first conversation we had. And now I'm going to have a second conversation which is like I don't know how you can be a VC and not believe markets are efficient.
51:43Like what are we doing like for capitalists? You have to believe markets are efficient. And so I think private markets are very efficient and private markets figure out the price. And so I just don't try and bet against the market. I think a lot of people think that whatever like the private markets aren't efficient and so you can find the deal and find the non-conensus deal. All of those deals were incredibly competitive and I didn't win by, you know, looking for a deal or whatever. I, you know, I mean, I I pay
52:12the market price and maybe I'll get a little discount because, you know, for negotiating or whatever, but I I never really worry about that. And so, as a productive investor, I just trust that the markets are actually pretty smart and I trust that the markets will value it at, you know, given risk adjusted.
52:27And I I I I believe that my diligence reduces that risk for me, but I I don't I don't do it on market value. I'm not trying to like find a better price. I'm just trying to find a less riskier asset.
52:39Doesn't it follow though that then the approach would be to just actually try to index the private markets like you just try to own literally the market weights of your Oh, I would love to, but you can't. I mean, you can't pragmat. I would love to. Of course. Of course. Yeah. So, this is right. This is right. So this is where this all lends to and and this is kind of like how we think about investing which is um um of course if I could have an index of every competitive like literally my my my dream would be I get 5% cognition when you buy cursor I I [laughter]
53:08every I've gotten 5% in every competitive and the only like I really believe private markets are super efficient. I do and I think that like the consensus is actually smart because I'm a capitalist and I believe in markets and so if I could have 5% of every competitive deal where you've got like legit investors in it and I'd be happy. But you you you simply cannot do that. You can't do that for competitive reasons. You can't do that for capacity reasons. So, as an investor, you have to come up with, you know, h how how do I like, you know, not run into the competitive bus, but even more
53:38importantly, like how do I not like run out of our ability to keep track and help these companies because listen, I I do take the boards, I do get very involved, very very involved, right? I mean, I you know, um and so like that's just impractical. So the way that we think about it, which you've heard before, but I'll restate it, is for every legitimate sector, and by that legitimate sector, we define it as there's good founders in it, because we don't second guess founders. If they're risking their futures and the opportunity costs and their family's wealth, then it's a good sector. We do
54:07the work to try and decide for every good sector, which is the top company.
54:12And that means you look at the team and you look at the tech and you look at the monetization potential, you look at the market growth potential, you look at all of that stuff and then we choose the best one and then we assume that the market is efficient. Like that's kind of the approach. So it's kind of an index but like we're actually segmenting it by market, you know, and sometimes we get it right and sometimes we get it wrong.
54:29But that way you're kind of indexing, you know, like the interesting markets.
54:32Yeah. There's this thing in indexing called stratified sampling from my old quantitative days. you can uh buy a small subset of the index and have your tracking error to the index be very low because you let actually literally what you're describing is effectively stratified sampling that you like get exposure to you know best biggest whatever per category and that will perform like similar to the Yeah. Okay. So that makes it and I mean I just you know I I just think it's funny like I think venture capital early
55:00on and I wasn't there I just read the books. I mean, I I think it believed that tech created value. So, it didn't overrow. I mean, often there was no there's no business to evaluate. And I just don't see so much hand ringing about bubbles or this or that or the other thing, right? I mean, like the market price is the market price. And so, like, you know, I to me there's always this huge dissonance in in when I'm talking with other investors where they're, you know, they they're always decrying the bubbles, which nobody can ever predict. Like like by definition, everybody's calling it a bubble. It's
55:30probably not a bubble. like it's almost like a bubble like when no when everybody's investing because they think there's still upsides. Um and then they don't somehow think private markets are efficient. Like remember I got like I got like VC canceled because I'm like non-consistent investing is dangerous.
55:44So like I once on Twitter was like hey listen I think it's it's it's dangerous to to to invest against consensus because like basically there's follow on capital risk. And from saying that, many prominent VCs came out [laughter] and they were like, you know, oh, like all of these deals that we've done were non-conensus. And I think there's something very kind of tied to the I I like the ego and the identity of of investors that they they have to believe that they they can truffle hunt and find the non-conensus thing, they're smarter than everybody else. But I think the
56:14reality is is certainly if you look at our portfolio, the ones that return money were actually very very competitive in general. So I just I just think these markets are actually quite efficient. In addition to this, like I love the idea of market efficiency and private markets being one area that you disagree maybe with lots of uh well-known apparently a lot.
56:30Apparently all of them. Um are there any other areas like that where you feel especially alone?
56:35Yes. [laughter] There's another one that drives me nuts. This is my last one, I promise.
56:41So another thing that drives me nuts is like this belief that if you put money in private markets, it doesn't somehow grow the t of private markets. I love Roloff at Sequo. I I think he's fantastic. He's incredibly intelligent guy. He's a great board member. But he gave this talk, do you remember at Techrunch um disruptor he's like and many many investors believe this. So this isn't to to call off rolloff because I was actually a huge fan of his, but he was like venture capital is not an asset class. There's only 20 startups that matter and that's it. And
57:10so if there's too much money going in, you've overfunded private markets. And to me, this is ludicrous. I mean like capital creates opportunities and markets and value and even though there is so much more money that has gone into the private markets in the last you know 20 years the value in the private markets has has kept pace right you've got massively large private companies tons of opportunities very large exits and so this zero someum
57:40thinking about private markets being like some amount of fixed again supply of great thing.
57:46It's so bizarre to like we're venture investors. We create value. Like tech creates value. If you put more money in it, it'll grow. And you will be surprised and maybe you won't be surprised. But I've been very surprised how common this mindset is. I'm very often I'll talk to a pretty senior GP who's been investing for 20 years and they'll be like, "Oh, there's too much money." I'm like, "What are you talking about? There should be more money in there. We need more more ecosystem, more value, more investment." So I I do don't I do believe money in private markets creates TAM. It creates the investable
58:16TAM. I think it creates value. I think there's more opportunity to deploy money now in private markets than ever has before. Even very simple examples of that are like companies not going public, right? Like if there's more private money available, why would you even go public, right? And so, you know, I think this again, we need to all step away from zero someum thinking. I think we all need to believe that like technology creates value. I think now, especially with AI, we need to believe that capital enables technology to create value. And if that's the case,
58:46more money in private markets, we [laughter] should deploy the money and we should create the value.
58:51Uh, you've been on, if you put this in NBA GM terms, you're like the the player that's like on fire. You can like jump really high with with between like cursor um and fifth phase company and Open Router, you know, all of these in a very short period of time. So, well done. But I I'm I'm more curious about the lessons you learned about M&A and kind of what's what's going on in this market having been a part of three of the maybe the three biggest major scale M&As in the last couple months.
59:19Yeah. So um so actually I I kind of have a history with strategic M&A going back to my company. So when I sold my company to VMware it was a $1.26 billion exit which at the time was the high I think I beat David Sax's Yammer. [laughter] It was the highest acquisitions on counting. Yeah.
59:38It was kind of funny because Catalyst Catalyst showed me this chart, you know, it was just kind of like multiples of revenue and like the total exit and there was like two outliers and it was like yeah company and they're like really close to each other. I was like marginally better [laughter] just a small bet at the time. I think that was the highest acquisition of multiples of revenue enterprise software. And then actually I was part of a deal that beat that which was the tabular acquisition to data bricks and then of course cursor I think it was the largest price fit acquisition ever. Um and of course you know FE acquisition was a very large acquisition. So I've
1:00:06done I've just I've just been a part of a lot of these kind of strategic M&A and so I think my comment only goes to strategic M&A and I'll say I've I've noticed a few trends. One of them is there's almost always like a like deep deep personal alignment. Um because you know it's it's it's a real risk for both sides. Like think like Lisa Sue and Fei or think Michael Truel and Elon or think like Alex and Patrick. I mean you almost
1:00:34always have people that have same visions of the future and they think about it the same way right whether it's you think in terms of markets or you thinks in terms of infrastructure or you thinks in terms of data. I mean that's almost always present is like there's some trust existing trust relation like existing alignment. The second one is you have to take it from the mind of the buyer. So what the buyer is doing is they're basically buying an option on a large market. Right? So in the case of like
1:01:02VMware buying Ner they're buying a $1 billion option on a $40 billion market.
1:01:07And so in order for that to make sense you kind of have to to solve the inductive proof for them. You have to show them the base case which is like you know we have this business that sells into networking and we can get that budget and then you have to do the inductive step and you guys have virtual machines so if we attach this to a virtual machine we can sell more and then therefore for part of you we can sell a whole bunch of these things. So you almost because they're buying a future option on a market you have to show
1:01:36the company's job is to show the inductive step the the company being acquired or both of them the the like the like like like the discussion clearing has to yeah the discussion the discussion for the M&A has to to be like you have the base case you have the inductive step therefore you can get this to this market which is like the large markets that happens and and that conversation in my experience is one kind of only founders can do and maybe investors that really really understand strategically
1:02:05what is going on, right? But those conversations are very it's almost like like really high stakes enterprise sales. I've been a part of a lot of also like more auctiony type M&A. You you never have those conversations. It's like you know like you're looking at the financial metrics and the spreadsheets and kind they're buying an asset etc.
1:02:22And so I just think they've got a very different flavor. [snorts] But I I think that especially with the timelines going down on tech, I think we're going to see more and more strategic exits. And so I think it's probably important for people to get pretty smart of how these things look. And and it's very different than they assume. Most people assume you should hire a banker and you should have an auction and get the highest price.
1:02:42And it's it's like hiring a banker is fine. You can do that if you want, but like the idea that you're gonna like go to like the apex predator, someone like whatever, Mark Zuckerberg, and play poker, like you're kidding yourself, right? like these things are built on trust and and telling out a story, not playing games or playing poker. And so I just think that there's kind of a mindset that you need to have if you're going to engage in these things is quite different than the intuition.
1:03:05So can you tell from your perspective the story of let's say the cursor since that's the biggest one of that acquisition since you're such an involved investor just like give us the story. We'd actually just we were just about ready to get a a raise done and we'd you raised a few billion dollars and like that was was um getting done.
1:03:21But this is about the time that Methos came out. Um and if you kind of worked backwards, you realize it probably cost I I don't know how much it costs, but it probably costs say $3 billion to make Mythos. And so we're like, you know, um if if Kurser is going to, you know, build models, we need to raise more money and get access to those computes.
1:03:40And um and so then of course that kicks off strategic discussions like there's not a lot of people that have access to that much compute. And so then you have those conversations. Um and then of course there's quite a bit of interest in the company as a result just because the company had like by far the most users and by far the most data. Um and so again this is one of these great examples where the you know in the end you know SpaceX had the compute um and cursor did have the data and had a team that had very successfully built you know models and built this practice and
1:04:09code was very important. So there's just a lot of alignment and and it always helps to have a a raise can because that helps actually set the value and set the price of these things. So that was actually a fairly straightforward um deal. I'm curious if there's anything similar lesson-wise from open router or from FA's company world labs and anything else that is sharable from those two experiences that might be indicative of or bear some lessons from
1:04:37this kind of strategic M&A. So, I'm going to go back to what I said, which is um for these strategic the most important thing is the the intuition especially of a lot of investors is there's a deal going down. We need to like play games. We need to leak it to the press. Drives me nuts. Um you know, we need to get other we need to get other companies in. And you don't realize like you're literally dealing with the most sophisticated people on the planet. Like I just don't think you walk up to Zuckerberg, you're like, "Oh, like I'm going to beat you in poker,
1:05:07dude. Like I'll take out your sucker and pat you on the head. I'm kidding. Like I'm not kidding. Right.
1:05:11It's like like these are the like these and so in every one of these deals the companies in very good faith and these are world record deals in very good faith engaged with the buyers. They didn't play any games and they knew that they were worth a certain amount of money because you know they had done raises or there were market comps and there was a lot of trust and having now done so many of these deals I've just
1:05:39found that that approach for strategic M&A is the right approach and I've been part of deals that are that size that have fallen apart because you know somehow a board member got into the head of the founder that oh you need to like get competive better. You got to leak it to the I mean I would think like I mean God the open router deal drove me nuts like it got leaked. Did you notice by the way that World Labs did not get leaked?
1:06:01Yeah. Interesting.
1:06:03Didn't get leaked because we didn't tell anybody. It was like me and there's a few people not leaked. Open router was leaking constantly, right? And I think that like a number of VCs think, oh, this is how you drive up the price or this is how you get it done. And you you see these things leak all the time. That destabilizes deals. Having done all these deals, it destabilizes deals. So again, I think the most important thing is a structural thing like your intuition as an investor in particular that this is like some commodity asset and it's about playing poker. It's just
1:06:32wrong. If it's strategic deal for a lot of money, I think you need to view it with very professionally. I think you need to develop a trust relationship. I think you need to do it in good faith. You should not leak that, you know, leak these deals. Um and realize that the people that you're are that are counterparties to this are the most sophisticated people in the industry.
1:06:50And and I I would say that in the founders in every one of these cases treated it that way. Michael Troll treated it that way and the team, you know, Alex and Chris treated it that way for Open Router. Um and uh for sure Fay treated that way.
1:07:02How are you seeing the role of investors evolve? Um both literally how it's evolving, you know, across these many many boards that you're on, but also some commentary on if you think investors generally of your type are doing a good job or or actually helping companies. It seems like because the stakes are so high, growth is so big, capital, the capital dollar amounts are so big that all these investors are overseeing it's kind of crazy. You maybe some commentary on like the role of the investor.
1:07:28One thing I will say is like venture is not what it used to be and and the startup ecosystem is not what it used to be. I mean if you look at the largest private companies right now, they would rival any public companies um you know 20 years ago, right? think like stripe or like data bricks or like spacics before it IPOed or ander roll or like I these companies are massive and so I think that one of the problems is is what it means to be a startup has shifted so much that now you have this
1:07:57undefined quagmire of like who should probably be public investors like you know investing in early stage startups and I just don't think those intuitions are are right and so I think that's kind of the root of like the the confusion. I think maybe it just actually makes sense to like start delineating a bit more on the on on the private side or if you know you have later stage people investing in earlier stage companies
1:08:25maybe a little bit more self-awareness like for example you wouldn't put me on a mining company board right I mean like I mean so some of these like I mean remember 2021 so remember 2021 we'd have like these like PE investors they would invest in these serious P companies I would sit on the board with these people and it's like it's literally like putting me on the board of a mining company. [laughter] I had no idea like like trying to like reason about the company through like burn like dude [laughter] you're going to be miserable here cuz
1:08:54all we do is burn cash for a long time and so it's more kind of the blending of the lines because private companies are a real asset class for latestage investors. You know I think listen I think a lot of this is just growing pains like how much larger do you think the market is now than it was 30 years ago?
1:09:13thousand times. So, of course, of course, you know, the industry is going to have to mature around that. And of course, you're going to have to like view it like a kind of later stage investor, of course. But I I I just think that um there's like an this funny identity crisis with a lot of like later stage investors, you know, who who view the world that way just because they're in private markets and their VCs think that, you know, all of a sudden now, you know, like for example, I would never invest in a late stage company. Like I don't think it goes the other like what would
1:09:42I do? I go there and you know tell you how to like run a finance oper. It's just not it's just not me. So I think that's it. It's just like it's basically the encourage of traditional banking and traditional finance and venture which absolutely belongs there. I just think sometimes it kind of reaches a little bit too low and then you kind of have these issues. You have these issues in M&A where they're like whatever let's like run an auction and let's like do all this other stuff or you know you have it in the operations of a company where like you know you're 20 people and they're worried about burn you know or
1:10:10like they're over rotating on metrics for disruptive technology. I just feel like we need to kind of bring back traditional productive VC for some subset of this and there's enough market for everyone. Has anything changed about how when you meet somebody for the first time, if like if I came and watched 10 meetings in a week with you 10 years ago when you started and then I came today and watched 10 meetings with you.
1:10:31Have you changed how you conduct your inter your early interactions with founders?
1:10:38Yeah, a lot. I mean, I I think most investors go through this, especially if you come from the operating world, like you have to learn how to listen as an investor. Um, and then you also have to learn how to ask the questions that you really care about so that you can kind of answer the questions to yourself. It's a very delicate balance, right? And um I do feel like a lot of like meetings with
1:11:08founders tend to be pretty performative on both side. Like you don't know what to ask and so you'll be like who's your competition? And then a lot of it is just asking questions for asking questions sake but like it doesn't actually inform your decision. Um and then especially if you're an operator, you'll hear something you disagree with and you kind of want to fix that problem, but that's kind of not your job. And so I think I I I have learned and I'm not perfect but and I I see there's a lot of junior like investors
1:11:36that come in that you know the primary job is just to listen and and like a founder will tell you what they believe right and so like if you disagree you disagree but like that's what they believe. I mean it's so often they'll say something like well but I would do it better and therefore like it's a good investment and then the the the and it's it's a truly an art. The second one that I mentioned is truly an art like you have to make a decision based on that meeting. There's a lot of silly questions you could ask that are not really going to inform that decision.
1:12:01What if Amazon does that? What is OpenAI? Like whatever. You can answer that yourself. Like like maybe you can like figure out how they think, but there are key questions that you really want to know and kind of knowing which ones those are during the time of the meeting and getting those in is a kind of a hard thing to do. And I think I've really kind of refined my ability to do that.
1:12:18Maybe a fun place to close is just to ask what has you most excited? We've talked about lots of the magic of this new era of technology and things that weren't possible before, bottlenecks that are now gone. I I know all of that excites you, but if you had to just step all the way back and uh describe why this job is so incredibly fun right now and why you're most excited, how would you frame it?
1:12:41I'm more and more of the belief that this is an industrial revolution level shift. And for me the industrial revolution went from basically a zero sum world to like a you know um nonzero sum where value is being created net new value is being created. And I think this is a very similar shift where before to solve problems you had to solve very complex engineering problems which basically didn't scale and were very tough and then you'd have to maintain them and that's why all software has always sucked to like basically being a capital problem. Like
1:13:10I think that for I don't know about the real world yet. I think we'll get there, but I think like we've turned this into a capital resourcing problem and we're capital allocators. And so I just feel like we're just in this very very strategic position to help drive the future in a much much more direct way than we ever have been before because I think this is a scaleup capital game that causes that to happen.
1:13:33I don't believe private markets have limited TAM. I think they have unlimited TAM and the more money that goes into them, the more value that would be created. So, I just feel like we're in this very privileged position, you know, very very key to the innovation chain and uh we're both very lucky to be here.
1:13:49I love the every two-year schedule that we're on. I hope we get to do it again in another two years. I can only imagine what the world's going to look like two years from now.
1:13:57We'll we'll have our Grockbox talk.
1:13:58[laughter] Thank you so much for your time.
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